In the last decade, advances in high-throughput technologies such as DNA microarrays
have made it possible to simultaneously measure the expression levels of tens of thousands …

High-throughput tools for nucleic acid characterization now provide the means to conduct
comprehensive analyses of all somatic alterations in the cancer genomes. Both large-scale …

Purpose: Genomic profiling studies suggest that triple-negative breast cancer (TNBC) is a
heterogeneous disease. In this study, we sought to define TNBC subtypes and identify …

Although targeting cancer metabolism is a promising therapeutic strategy, clinical success
will depend on an accurate diagnostic identification of tumor subtypes with specific …

In this paper, we demonstrate a computationally efficient new approach based on deep
learning (DL) techniques for analysis, design and optimization of electromagnetic (EM) …

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix
Factorization (NMF). This includes NMF's various extensions and modifications, especially …

Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-
based, linear representations of non-negative data. Although it has successfully been …

We describe here the use of nonnegative matrix factorization (NMF), an algorithm based on
decomposition by parts that can reduce the dimension of expression data from thousands of …

Abstract Background Nonnegative Matrix Factorization (NMF) is an unsupervised learning
technique that has been applied successfully in several fields, including signal processing …